Student Attendance Monitoring System Using Face Recognition
7 Pages Posted: 24 May 2021
E CHARAN SAI
Jain University, Faculty of Engineering & Technology, School of Engineering and Technology
SHAIK ALTHAF HUSSAIN
Amara shyam.
Date Written: May 22, 2021
There is no reason that a critical educational practise like attendance should be viewed in the old, tedious manner in this age of rapidly evolving new technologies. In the conventional method, it is difficult to manage large groups of students in a classroom. Since it takes time and has a high risk of error when entering data into a system, it is not recommended. Real-Time Face Recognition is a practical method for dealing with a large number of students' attendance on a daily basis. Many algorithms and techniques have been developed to improve face recognition performance, but our proposed model employs the Haarcascade classifier to determine the to determine the positive and negative characteristics of the face, as well as the LBPH (Local binary pattern histogram) algorithm for face recognition, all of which are implemented in Python and the OpenCV library. For user interface purposes, we use the tkinter GUI interface.
Keywords: Local Binary Pattern Histogram(LBPH), Face Detection, Face Recognition, Haarcascade Classifier, Python, Student Attendance.
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E CHARAN SAI (Contact Author)
Jain university, faculty of engineering & technology, school of engineering and technology ( email ).
Bangalore, 572112 India
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Attendance Management System Using Face Recognition
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- I. G. Vishnu Vardhan 12 ,
- M. Ajay Kumar 12 ,
- P. Nithin Kalyan 12 ,
- V. Spandana 12 &
- J. Ebenezer ORCID: orcid.org/0000-0002-2638-9961 12
Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 672))
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Today’s educational institutions are concerned with students’ ongoing performance. One problem causing the reduction in student performance is the insufficient attendance. The most well-known methods of recording attendance include calling or signaling the students. It got harder and took longer. It is now necessary to have a computer-based student attendance monitoring system that enables the teacher to keep attendance records. In this project, we employed a clever face recognition-based attendance system. We have recommended setting up a “multi-use attendance management system using face recognition” in the area. Face permission allows for facial recognition in modern implementations, which reduces time and eliminates the possibility of proxy attendance. Additionally, this establishes when a particular predefined order was inserted, information on their presence. This project is implemented using Python, and development is done using PyCharm. The face landmark estimation set of guidelines is used in our work. Finding their faces and recording their attendance is the difficult part. This method eliminates the possibility of fake attendance because it uses the face as a biometric for authentication.
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Vishnu Vardhan, I.G., Ajay Kumar, M., Nithin Kalyan, P., Spandana, V., Ebenezer, J. (2023). Attendance Management System Using Face Recognition. In: Suma, V., Lorenz, P., Baig, Z. (eds) Inventive Systems and Control. Lecture Notes in Networks and Systems, vol 672. Springer, Singapore. https://doi.org/10.1007/978-981-99-1624-5_64
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Published : 15 June 2023
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Abstract and Figures The paper argues that maintaining regular attendance is crucial for student success, and traditional attendance management methods can be inefficient and time-consuming for ...
Face is one of the most broadly used biometrics for human identity authentication. This paper presents a facial recognition attendance system based on deep learning convolutional neural networks. We utilize transfer learning by using three pre-trained convolutional neural networks and trained them on our data.
Keywords: Local Binary Pattern Histogram (LBPH), Face Detection, Face Recognition, Haarcascade Classifier, Python, Student Attendance. undefined Suggested Citation: SAI, E CHARAN and HUSSAIN, SHAIK ALTHAF and KHAJA, SYED and SHYAM, AMARA, Student Attendance Monitoring System Using Face Recognition (May 22, 2021).
A facial recognition-based attendance system operates in the following steps: (1) capture the image, (2) detect the face, (3) recognize it with the database, and (4) mark the attendance ...
Recognition of the human face is an active issue for authentication purposes specifically in the context of attendance of students. Attendance system using face recognition is a procedure of recognizing students by using face biostatistics based on the high definition monitoring and other computer technologies.
Efficient Real-Time Face recognition-based attendance systems with deep learning algorithms strive for precise and real-time performance in managing attendance across various institutions. This solution outlines key targets as well as robust face detection, model selection, real-time processing, information collection, and ensuring accuracy and reliability in face recognition by combining dlib ...
Abstract Face recognition has been a hot topic of research for a long time. Face recognition is a difficult problem to solve and that is what attracts researchers toward it. Automated attendance system is a practical application of face recognition technology.
This research paper explores the development and implementation of an Automated Face Recognition Attendance System using deep learning methodologies. By harnessing the power of deep learning algorithms, the system aims to automate the attendance tracking process, eliminate manual data entry, and enhance accuracy and reliability.
Face recognition technology is useful because it can use a person's unique facial characteristics as biometrics. Tracking who was present when is often the most challenging part of the job. Teachers traditionally have taken attendance by calling out students and recording their physical presence or absence.
Abstract—The current approach to marking attendance in colleges is tedious and time consuming. I propose AttenFace, a standalone system to analyze, track and grant attendance in real time using face recognition. Using snapshots of class from live camera feed, the system identifies students and marks them as present in a class based on their presence in multiple snapshots taken throughout the ...
Abstract This research paper mainly deals with the modern attendance system using Facial Recognition to improve the accuracy of attendance details. It uses a webcam or other camera to detect the ...
ABSTRACT: The main purpose of this project is to build a face recognition-based attendance monitoring system for educational institution to enhance and upgrade the current attendance system into more efficient and effective as compared to before. The current old system has a lot of ambiguity that caused inaccurate and inefficient of attendance taking. Many problems arise when the authority is ...
This paper introduces a Facial Recognition Attendance Monitoring System designed to address the limitations of conventional attendance tracking methods. The system leverages cutting-edge advancements in computer vision and machine learning to provide a robust and reliable mechanism for recording attendance.
In summary, a smart attendance system using face recognition technology revolutionizes the traditional attendance management process by offering a reliable, convenient, and secure solution.
Abstract This Review Paper studies several research papers based on the Smart Attendance system for recording attendance based on facial recognition. Efficient and accurate attendance management is a crucial task in various educational and organizational settings. Traditional methods of manual attendance tracking are time-consuming and error-prone. The proposed system utilizes computer vision ...
In most recent times, the Face Recognition technique is widely used in University automation systems, Smart Entry management systems, etc. In this paper, a novel CNN architecture for face recognition system is proposed including the process of collecting face data of students.
This model includes a camera that captures an input image, a face detection technique, face identification and encoding, recording attendance in a spreadsheet, and exporting the spreadsheet as a PDF file. The training database is created by educating the system using the faces of the authorized students.
Smart attendance management system is designed to solve the issues of existing manual systems. We have used face recognition concept to mark the attendance of student and make the system better. The system performs satisfactory in different poses and variations.
The face is the most important thing which identifies a human. Therefore, in this paper, we work on an attendance system using a face detection algorithm in real-time using the frontal face recognition concept. In this paper, we describe an efficient algorithm of haar cascade using an open-source image processing framework known as OpenCV.
The purpose of this research study is to investigate the idea, creation, and use of an Attendance Management System (FRAMS) based on facial recognition. This study's main goals are to describe the technology underlying facial recognition, go over the benefits and drawbacks of FRAMS, assess how it affects attendance control in different ...
PDF | On May 30, 2020, Dr. Sabeenian R.S and others published Smart Attendance System Using Face Recognition | Find, read and cite all the research you need on ResearchGate
This paper designs and develops an attendance system based on RFID (Radio Frequency Identification Devices, RFID) and face recognition. By utilizing a composite authentication method with high recognition, the reliability of attendance management and the accuracy of attendance certification are enhanced.
Abstract - Identification of any peoples in any organization or colleges for the purpose of attendance marking is one such a software of face recognition. The use of Attendance Management System is to performs the regular activities of attendance marking and analysis with reduced human intervention. In this method the camera is settled and it will capture the image, the faces are recognize ...